The purpose of this project is to conduct research in statistical methods and computer techniques with particular emphasis on those appropriate for analyzing data from clinical, diagnostic, and prevention trials and epidemiologic studies of cancer. Many of the problems studied under this project arise from the consultative activities of the Section. Important activities during the past year have included investigating methods for analyzing complex sample survey data, including ways of incorporating the clustering and weighting of the observations into regression analyses of epidemiologic studies, and approaches to analyzing data from large national health surveys such as the National Health and Nutrition Examination Surveys (NHANES) and the National Health Interview Surveys (NHIS); analyzing dietary survey data using a statistical model incorporating a mixture of abstainers and consumers, which relates abstention and average consumption to covariates; developing a computer model for assessing the effects of population-based cancer screening programs; using permutation tests for analyzing disease progression based on patient status measurements at fixed time points; and fitting proportional hazard models to survival data for patients with colorectal cancer to identify prognostic factors and thus to predict survival for future patients, as well as comparing this approach to other proposed statistical methods. Finally, the Section has continued to maintain and improve software for interactive analysis of complex medical data using sophisticated multiple regression techniques and survival analysis. These programs are operational on the NIH Convex Computer system.